Overview

This is a basic introduction to the mapview packaged developed by Tim Appelhans and others. For more information on the package and even more tutorials check out https://r-spatial.github.io/mapview/index.html

Setup

You will need the sf, mapview and raster packages.

knitr::opts_chunk$set(echo = TRUE, warning = F, message = F)

library(sf)
library(mapview)
library(raster)

Load spatial data

Point data

The sb-tweets shapefile is a spatial dataframe of tweets from Santa Barbara between September & November of 2019.

sb_tweets <- read_sf("data/sb-tweets.shp")

Time for mapview

mapview(sb_tweets)

Play with color

mapview(sb_tweets, zcol = "usr_typ")
mapview(sb_tweets, zcol = "Month")

Playing with continuous (using days here which isn’t usually what you would do)

mapview(sb_tweets, zcol = "Day")

Polygon data

The California Protected Areas Database (CPAD) can be downloaded at: https://www.calands.org/. I’ve already cropped it to the Santa Barbara area, and selected just a few of the columns, but the full dataset covers the entire state and has a lot more information.

#read in data
cpad <- read_sf("data/ca_protected_areas.shp")

#simple view
mapview(cpad)

You can play with color using the zcol argument to set the variable to color by. In this case we will use Access Type.

mapview(cpad, zcol = "ACCESS_TYP")

By adding burst = TRUE to the mapview function you can split out a variable into unique layers according to all unique values of the variable

mapview(cpad, zcol = "ACCESS_TYP", burst = TRUE)

You can set your own color palette or even discrete colors using the col.regions argument.

mapview(cpad, zcol = "ACCESS_TYP", col.regions = c("purple", "yellow", "darkgreen", "orange"))
mapview(cpad, zcol = "ACCESS_TYP", col.regions = mapviewPalette("mapviewSpectralColors"))

Easily combine layers using the +, and set label titles.

mapview(cpad, zcol = "ACCESS_TYP", layer.name = "CPAD Access") + 
  mapview(sb_tweets, zcol = "usr_typ", layer.name = "SB Tweets", col.regions = c("darkgreen", "darkblue"))

You can change the basemap and also turn on and off layers that you’ve added to the map using the controls on the left hand side of the map.

Raster

You can also plot raster data. The data here is fish catch in tons/km2 for the US Northeast region from 2015. It’s a big raster but mapview scales it for viewing. As you hover over the cells you see the value pop up on the top right portion of the map.

catch <- raster("data/catch_2015.tif") 

mapview(catch)

Save with mapshot

You can use the mapshot argument to save a map either as an interactive .html to share with others or post online, or a static png. When I first tried this I got a PhantomJS error:

PhantomJS not found. You can install it with webshot::install_phantomjs(). If it is installed, please make sure the phantomjs executable can be found via the PATH variable.

and had to install it before it worked…

#first name the map

map <- mapview(sb_tweets, zcol = "usr_typ")

mapshot(map, file = "sb_tweet_map.png")